学术报告（7月20日）

主持人： 张笑 教授

欢迎广大师生踊跃参加！

报告摘要：
The confluence of disruptive technologies beyond CMOS and "Big Data" workloads calls for a fundamental paradigm shift from homogenous compute-centric system to heterogeneous data-centric system for better innovation, competition and productivity. With the objective of rethinking data-centric system from ground up, through a concrete example, I will show how to leverage emerging memory technology such as phase-change memory (PCM) to realize a new IC building block for future data-centric system. A novel chip was designed and fabricated for the first time. It fundamentally blurs the boundary between computation and storage, i.e., it can either be configured as a compute unit - a high performance search engine or as a storage media - storage class memory. It achieves >10x area reduction compared to homogenous CMOS-based design at the same technology node and reliably operates at ultra-low voltage down to 750mV. In the talk I will briefly highlight a few critical enabling techniques from material, circuit, architecture and algorithm perspectives. I will also show a roadmap on how to scale current design into future generation based on variable-bit storage. The proposed concept is applicable to other emerging nonvolatile memory technologies such as resistive memory, etc.

报告人简介：

Dr. Jing Li is an assistant professor at the ECE department of University of Wisconsin Madison. She spent her early career at IBM T. J. Watson Research Center as a Research Staff Member from 2009 to 2014. Her general research interest is developing new computing paradigm driven by either technologies or workloads or both. Her primary area of interests is "everything about memory" with a strong emphasis on “design for transformation” rather than “design for replacement”, including but are not limited to new computing concepts/models (e.g., near-/in-memory computing, associative/cognitive computing, reconfigurable computing, etc.), hardware prototyping, memory/storage subsystem, memory architecture and interface protocol, circuit design and CAD methodology, memory technology (device/integration/material), etc. that can transform today's hardware-software hierarchy. The key differentiator of her research is that besides modeling and simulations, she puts additional emphasis on real hardware demonstration through architecting, designing and testing new hardware prototypes. Previously, she demonstrated the world's first heterogeneous chip that fundamentally blurs the boundary between computation and storage. The work was recognized as a highlighted paper by Symp. on VLSI Circuits 2013 and an invited paper for JSSC'14.

She has received IBM Research Division Outstanding Technical Award in 2012 for successfully achieving CEO milestone, multiple invention achievement awards and high value patent application awards from IBM from 2010-present, IBM Ph.D. Fellowship Award in 2008, Meissner Fellowship in 2004 from Purdue University, etc. She has published more than 35 technical papers in referred journals and conferences and has more than 35 patents filed/issued. She won the Best Paper Award from IEEE Circuits and Systems Society VLSI Transactions for her contribution in STT RAM. She has been serving in organizing committee for a premier industry conference - International Memory Workshop (IMW) as finance chair and technical chair in 2014 and 2015, respectively. She is currently the general chair for IMW 2016. She has also been serving on the technical committee for Design Automation Conference (DAC), International Conference on Computer‑Aided Design, International Symposium on Circuits and Systems (ISCAS) and on NSF panels.  Besides academic impacts, her contributions to IBM’s IP portfolio have been essential to multiple lucrative partnerships. Dr. Li received PHD degree from Purdue University in 2009 and BE degree from Shanghai Jiao Tong University in 2004.

Dr. Bing Dai is a researcher at the Laboratory for Optical and Computational Instrumentation (LOCI), University of Wisconsin - Madison. He is currently leading the effort of developing an FPGA-based microscopy system with advanced real-time image processing capabilities for cancer detection and diagnosis. Before joining LOCI, he worked as an Advisor Engineer at Computational Lithography department, IBM Semiconductor Research and Development Center from July 2011, responsible foradvanced optical proximity correction and process modeling for key mask levels of the latest five generations of IBM silicon technologies (32nm to 7nm). Before that, he was a post-doc researcher at Nanofabrication and Electron Beam LithographyDepartment at IBM T. J. Watson Research Center. Dr. Dai's general research interest is novel imaging and nanofabrication, with a strong emphasis on close interaction between  hardware innovation and software advancement. His primary area of interest is developing hardware-accelerated software platform for biomedical imaging. He has been reviewers of numerous journals and conferences, and has been serving on the Program Committee for the International Conference on Electron, Ion, and Photon Beam Technology and Nanofabrication (EIPBN, the premier conference on the science and technology of nanopatterning) since 2013.  He received his PhD degree in Applied Physics and MS degree in Electrical Engineering in 2010 and 2009 respectively from Stanford University, and BS degree from Peking University in 2005.